NumPy Getting Started

🚀 NumPy — Getting Started

NumPy is a Python library used for working with arrays, numbers, and mathematical operations. Before using NumPy, you must install and import it.


📦 1. Installing NumPy

Using pip:

pip install numpy

Using conda:

conda install numpy

If NumPy is already installed, Python will recognize it during import.


📥 2. Importing NumPy

The standard way to import NumPy is:

import numpy as np

Using np is a shortcut so you don’t type numpy every time.


📌 3. Creating Your First NumPy Array


 

Output:

[1 2 3 4 5]

🔍 4. Checking NumPy Version


 


🧮 5. NumPy Arrays vs Python Lists

Python list:


NumPy array:


NumPy arrays are:

✔ Faster
✔ Require less memory
✔ Allow vectorized arithmetic operations

Example:


Output:

[ 2 4 6 8 10]

(You cannot do this easily with normal Python lists.)


📚 6. Creating Different Types of Arrays

➤ Array of zeros


Output:

[0. 0. 0. 0. 0.]

➤ Array of ones


Output:

[[1. 1. 1.]
[1. 1. 1.]]

➤ Generate sequence (like Python range())


Output:

[1 3 5 7 9]

➤ Generate evenly spaced values


Output:

[0. 0.25 0.5 0.75 1. ]

📏 7. Checking Array Attributes


 


✔ Summary

Task Example
Install NumPy pip install numpy
Import NumPy import numpy as np
Create array np.array([1,2,3])
Special arrays np.zeros(), np.ones(), np.arange()
Check version np.__version__

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